The Treatment Section has been engaged in a long-term project to improve treatment for substance dependence through behavioral, pharmacologic, or combined behavioral and pharmacologic interventions. Cocaine users not seeking treatment have increased regional brain mu-opioid receptor (mOR) binding that correlates with cocaine craving and tendency to relapse. In cocaine-abusing outpatients participating in treatment, the relationship of mOR binding and treatment outcome is unknown. Therefore, we determined whether regional brain mOR binding prior to treatment correlates with outcome and compared it to standard clinical predictors of outcome. Twenty-five individuals seeking outpatient treatment for cocaine abuse or dependence (DSM-IV) received up to 12 weeks of cognitive-behavioral therapy and cocaine-abstinence reinforcement whereby each cocaine-free urine was reinforced with vouchers redeemable for goods. Regional brain mOR binding was measured before treatment using positron emission tomography (PET) with 11C carfentanil (a selective mOR agonist). Main outcome measures were: 1) overall percentage of urines positive for cocaine during the first month of treatment, 2) longest duration (weeks) of abstinence from cocaine during treatment, all verified by urine toxicology. Elevated mOR binding in the medial frontal and middle frontal gyri before treatment correlated with greater cocaine use during treatment. Elevated mOR binding in the anterior cingulate, medial frontal, middle frontal, middle temporal, and sub-lobar insular gyri correlated with shorter duration of cocaine abstinence during treatment. Regional mOR binding contributed significant predictive power for treatment outcome beyond that of standard clinical variables such as baseline drug and alcohol use. Elevated mOR binding in brain regions associated with reward sensitivity is a significant independent predictor of treatment outcome in cocaine-abusing outpatients, suggesting a key role for the brain endogenous opioid system in cocaine addiction. This information could be useful for developing new treatment and diagnostic approaches to cocaine dependence. Substantial effort has been directed to identifying the optimal parameters for delivering contingency management, a behavioral approach in which incentives are used to increase the frequency of desirable behaviors, such as drug abstinence or medication adherence. A major challenge associated with contingency management is its likely prohibitive cost and staff/resource intensity, especially when the reinforcement follows an escalating amount schedule. Workflow challenges include varying conditions for meeting inclusion criteria, stratification into various groups, tracking categories of reinforcers chosen, and determination of eligibility for bonus reinforcers based on laboratory results or other protocol-defined criteria. To address these challenges, in collaboration with the Biomedical Informatics Section of the NIDA IRP, we implemented the Automated Contingency Management (ACM) decision support system for abstinence reinforcement. We are continuing to improve the system and to develop mechanisms to make it available to community treatment programs. We have begun a project to field test the usability and robustness of an ACM program, eXtensible Platform for Motivational Incentives (XPMI), implemented under conditions simulating those of a community treatment program with limited technology support. The availability of such a system would promote technology transfer and increase community use of evidence-based procedures for abstinence reinforcement. In further technology-development work, we are exploring the use of handheld electronic devices for treatment delivery in patients daily environments. We have completed a pilot study using these devices to remind patients to complete homework assigned by counselors as part of cognitive-behavioral therapy. Analyses of the results are under way. We also remain committed to transforming our new descriptive approaches (such as GMA, described in the report for Z01000499) into interventions. For example, we have shown that electronic-diary studies can provide amazing insight into the daily lives of substance abusers during treatment and data that are sensitive to behavioral changes during even brief periods of abstinence. The technologies that enable us to collect data on drug use, craving and stress in the field may also be used for delivery of treatment in the field, perhaps in response to the patients'own self-reported behaviors or previously identified triggers. We are just beginning to pilot this challenging opportunity.